Sr. Data Scientist (Fraud Analyst)

Company Description

Achieve is a leading digital personal finance company. We help everyday people move from struggling to thriving by providing innovative, personalized financial solutions. By leveraging proprietary data and analytics, our solutions are tailored for each step of our member's financial journey to include personal loans, home equity loans, debt consolidation, financial tools and education. Every day, we get to help our members move their finances forward with care, compassion, and empathetic touch. We put people first and treat them like humans, not account numbers.

Job Description

We’re seeking a highly analytical, proactive Sr. Data Scientist / Fraud Rules & Strategy Analyst to join our fraud-prevention team. In this role you will own the development, maintenance and continuous improvement of our fraud rulesets, working in an agile manner to respond quickly to evolving fraud patterns. You will also engage external vendors and partners to bring the latest industry intelligence and emerging fraud-strategy thinking into our program. Your technical toolkit (Python, SQL, Tableau) will ensure data-driven rule design, performance monitoring and dashboarding. If you have 3 years of experience in fraud management, plus strong analytical and communication skills, this is an exciting opportunity to help shape a leading fraud-prevention capability.

Key Responsibilities

• Design, implement and maintain the fraud-detection and prevention rulesets across our transaction flows, updates made iteratively in an agile fashion (frequent, incremental rule releases).
• Monitor rule performance (false-positives, false-negatives, operational metrics) and adjust rules to optimize detection and minimize business friction.
• Execute ad hoc analysis of fraud trends, emerging typologies, and root‐cause investigations to identify opportunities for new or updated rules.
• Work closely with vendors (fraud-detection/analytics platform providers, third-party intelligence services) to incorporate current industry thinking and best practices into our strategy.
• Develop dashboards and reports in Tableau to visualize key fraud metrics, rule performance, business impact and risk exposure.
• Write SQL queries and Python scripts to interrogate transaction, alert and case data; build prototypes of new rules, test and deploy them.
• Collaborate cross-functionally with Product, Operations and Compliance teams to align fraud-prevention initiatives with business goals and regulatory requirements.
• Participate in sprint planning, retrospectives and backlog grooming to ensure fraud-rule work is aligned with the agile roadmap.
• Maintain documentation of rule logic, assumptions, test results and versioning; ensure auditability and traceability of rule changes.
• Stay apprised of fraud-prevention industry trends, vendor technology updates, and regulatory developments; provide recommendations to senior leadership for strategy refinement.

Qualifications

Minimum Qualifications

• Bachelor’s degree in quantitative discipline (e.g., Computer Science, Data Science, Finance, Economics, Mathematics) or equivalent.
• Minimum of 3 years of hands-on experience in fraud detection, fraud analytics, risk management or a related role (preferably in payments, fintech, e-commerce or banking).
• High level of proficiency in SQL and Python for data manipulation, data interrogation, scripting and rule prototyping.
• Proven experience with Tableau (or equivalent business-intelligence tools) to build dashboards and visualizations.
• Experience designing, deploying and maintaining fraud-detection rules/rule engines (or equivalent controls) and analyzing the results.
• Experience interacting with vendor solutions, engaging external partners or bringing in external intelligence to inform strategy.
• Excellent analytical, problem-solving and critical-thinking skills with attention to detail.
• Strong verbal and written communication skills – able to translate technical detail into actionable insights for business stakeholders.
• Comfortable working in an agile environment: attending sprint ceremonies, prioritizing tasks, responding to changing requirements.
• Ability to work independently, manage multiple concurrent rule-updates and investigations, while balancing business-friction vs risk mitigation trade-offs.

Preferred Qualifications

• Experience in rule-engine platforms specific to fraud (e.g., real-time transaction scoring, device/fingerprint, anomaly detection).
• Familiarity with account-takeover, synthetic identity and first and third party fraud typologies.
• Experience working with vendor-provided fraud intelligence or external data sources (device data, IP intelligence, user behavior).